Mining Digital Traces to Uncover Global Perception of Bali’s Topmost Destinations

Abstract

User generated content (UGC) provides abundant tourist information regarding destinations. The textual digital traces bring great opportunity along with great challenges. Text mining approaches including sentiment analysis, multiclass text classification, and network analysis are suitable for extracting the buried pattern under piles of unstructured data. We processed 18.721 reviews from worldwide tourists about Bali’s 15 topmost tourist attractions. This study uncovers the tourist perception through textual data using sentiment analysis to extract the positive and negative perceptions, and multiclass classification to extract the tourist cognitive concern for each destination. We discover the tourist visiting patterns deeper by combining perception tone and cognitive concern results using network analysis to map out the destinations’ popularity, interconnectivity, and major cognitive perception. Most of the tourists disclose positive expressions and give their concerns about Bali’s natural attractions. They feel best for the social setting and environment aspect, and worst for the accessibility. Sacred Monkey Forest Sanctuary is the most favorite destination and a potential point of a visit to other destinations. This research provides insight into the global perception of Bali’s topmost destinations for government and other tourism stakeholders to support the development and improvement of Bali’s tourism.